DeepSeek V4.1 Flash vs GPT-6 Luna vs GLM-5.3-Flash
Too close to call on our weighted score (GLM-5.3-Flash 79, GPT-6 Luna 78, DeepSeek V4.1 Flash 72). The right pick depends on what you value most.
DeepSeekDeepSeek V4.1 Flash
72/100- ECI155.0
- Price$0.15 / $0.60
- Context1M
OpenAIGPT-6 Luna
78/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
Z.ai (Zhipu)GLM-5.3-Flash
79/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
Too close to call
It is close. Our weighted score puts them within 1 points (GLM-5.3-Flash 79/100, GPT-6 Luna 78/100, DeepSeek V4.1 Flash 72/100), so choose by what matters most for your work: GPT-6 Luna on price and GPT-6 Luna for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · GLM-5.3-Flash $0.237 · DeepSeek V4.1 Flash $0.263 per 1M tokens (3:1 blend)
- Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · DeepSeek V4.1 Flash 1,000,000 · GLM-5.3-Flash 1,000,000 tokens
- Widest inputsGLM-5.3-FlashDeepSeek V4.1 Flash: Text, Images · GPT-6 Luna: Text, Images, PDFs · GLM-5.3-Flash: Text, Images, PDFs, Video
- Self-hostingDeepSeek V4.1 Flash and GLM-5.3-FlashPublishes downloadable weights (MIT)
| Measure | Weight | DeepSeek V4.1 Flash | GPT-6 Luna | GLM-5.3-Flash |
|---|---|---|---|---|
| Price | 50% | 77 | 83 | 79 |
| Inputs & features | 30% | 70 | 80 | 90 |
| Context window | 20% | 60 | 61 | 60 |
| Overall | 100% | 72/100 | 78/100 | 79/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4.1 FlashDeepSeek | GPT-6 LunaOpenAI | GLM-5.3-FlashZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.0 (best) | — | 151.9 |
| ECI rank | #29 of 148 (best) | — | #42 of 148 |
| GPQA DiamondGraduate-level science questions | — | 90.5% (best) | 90.2% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 79.0% (best) | 55.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 98.9% (best) | 93.9% |
| SimpleQA VerifiedShort factual questions | — | 41.4% | — |
| Price per million tokens | |||
| Input | $0.15 | $0.10 (best) | $0.15 |
| Output | $0.60 | $0.50 (best) | $0.50 (best) |
| Cached input | $0.003 (best) | $0.01 | $0.03 |
| Blended (3:1) | $0.263 | $0.20 (best) | $0.237 |
| Long-context rate | Same rate | Over 272K: $0.20 / $0.75 | Same rate |
| Price source | Official DeepSeek API | Official OpenAI API | Official Z.AI API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,050,000 tokens (best) | 1,000,000 tokens |
| Max output | 384,000 tokens (best) | 128,000 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · high · max | Yeslow · medium · high · xhigh · max | Yeslow · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | OpenMIT | Proprietary | Open |
| API model ID | deepseek-flash | gpt-6-luna | glm-5.3-flash |
| API providers | 50 | 24 | 65 (best) |
| Released | Sep 10, 2026 | Sep 22, 2026 | Aug 26, 2026 |
| Knowledge cutoff | May 2025 | May 18, 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek V4.1 Flash$2.70
- GPT-6 Luna$2.00
- GLM-5.3-Flash$2.50
Which should you choose?
Which is better: DeepSeek V4.1 Flash, GPT-6 Luna or GLM-5.3-Flash?
It is close. Our weighted score puts them within 1 points (GLM-5.3-Flash 79/100, GPT-6 Luna 78/100, DeepSeek V4.1 Flash 72/100), so choose by what matters most for your work: GPT-6 Luna on price and GPT-6 Luna for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek V4.1 Flash, GPT-6 Luna or GLM-5.3-Flash?
GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). GLM-5.3-Flash costs $0.15 input / $0.50 output per million tokens (official Z.AI API price); DeepSeek V4.1 Flash costs $0.15 input / $0.60 output per million tokens (official DeepSeek API price). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for GPT-6 Luna versus $0.237 for GLM-5.3-Flash (1.2× as much) and $0.263 for DeepSeek V4.1 Flash (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek V4.1 Flash has an ECI of 155.0, GPT-6 Luna has not been scored yet and GLM-5.3-Flash has an ECI of 151.9.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4.1 Flash, GPT-6 Luna and GLM-5.3-Flash yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-6 Luna has the largest context window at 1,050,000 tokens, against 1,000,000 for DeepSeek V4.1 Flash and 1,000,000 for GLM-5.3-Flash. Maximum output per response: DeepSeek V4.1 Flash up to 384,000, GPT-6 Luna up to 128,000, GLM-5.3-Flash up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4.1 Flash accepts text and images; GPT-6 Luna accepts text, images and PDFs; GLM-5.3-Flash accepts text, images, PDFs and video. GLM-5.3-Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek V4.1 Flash and GLM-5.3-Flash publishes its weights (MIT) and can be self-hosted; GPT-6 Luna is proprietary.
Which is newer?
GPT-6 Luna is the newest, released Sep 22, 2026. DeepSeek V4.1 Flash came out Sep 10, 2026; GLM-5.3-Flash came out Aug 26, 2026. Knowledge cutoff: DeepSeek V4.1 Flash May 2025, GPT-6 Luna May 18, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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